Determinants of Electricity Consumption Intensity in China: Analysis of Cities at Subprovince and Prefecture Levels in 2009
Table 4
Estimation results and variable structure for the finite mixture modela.
Variable
Structure
Coefficient estimates
Component 1
Component 2
Component 3
Component 4
Predictor
Intercept
Varied
5461.407*** (919.115)
379.656*** (87.482)
1774.662*** (158.055)
982.128*** (61.198)
Varied
113.915*** (40.749)
23.923*** (2.821)
59.830*** (6.378)
40.738*** (3.021)
Varied
66.189 (92.219)
22.124*** (6.895)
48.875*** (12.326)
32.844*** (4.232)
Fixed
−9.677** (4.896)
−9.677** (4.896)
−9.677** (4.896)
−9.677** (4.896)
Nested
19.305*** (7.366)
19.305*** (7.366)
17.365** (6.991)
17.365** (6.991)
Varied
−7.509*** (1.315)
−0.287 (0.185)
−2.910*** (0.414)
−0.759*** (0.130)
Varied
−52.716 (35.108)
6.815** (2.750)
25.498*** (7.160)
−7.531*** (1.774)
Concomitant variable
Intercept
Varied
—
2.187*** (0.441)
1.976*** (0.473)
2.285*** (0.516)
Varied
—
−0.032*** (0.012)
−0.062** (0.024)
−0.186** (0.092)
aThe standard errors of coefficient estimates are in parentheses. ** and *** denote significance at 5% and 1% levels, respectively. All the explanatory variables are standardized.